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The purpose of this study is to seek to re-examine the threshold effects of public debt on economic growth in Africa.

This study applies panel smooth transition regression approach advanced by González et al. (2017). The method allows for both heterogeneity as well as a smooth change of regression coefficients from one regime to another.

A debt threshold in the range of 62–66% is estimated for the whole sample. Low debt is found to be growth neutral but higher public debt is growth detrimental. For middle-income and resource-intensive countries, a debt threshold in the range of 58–63% is estimated. As part of robustness checks, a dynamic panel threshold model was also applied to deal with the endogeneity of debt, and a much higher debt threshold was estimated, at 74.3%. While low public debt is found to be either growth neutral or growth enhancing, high public debt is consistently detrimental to growth.

The findings of this study show that there is no single debt threshold applicable to all African countries, and confirm that the debt threshold level is sensitive to modeling choices. While further analysis is still needed to suggest a policy, the findings of this study show that high debt is detrimental to growth.

The novelty of this study is twofold. Contrary to previous studies on Africa, this study applies a different estimation technique which allows for heterogeneity and a smooth change of regression coefficients from one regime to another. Another novelty distinct from the previous studies is that, for robustness checks, this study divides the sample into low- and middle-income countries, and into resource- and nonresource intensive countries, as debt experience can differ among country groups. Further, as part of robustness checks, another estimation method is also applied in which the threshold variable (debt) is allowed to be endogenous.

The aim of this article is to research on forestry green total factor productivity and explore the impact of financial support on forestry green total factor productivity.

The methods used in this study are super efficiency SBM model of undesired output and empirical model. SBM model is a kind of Data Envelopment Analysis (DEA). The SBM model with non-expected outputs (slacks-based measure) can be used to deal with the problem of efficiency measurement with multiple input and output variables and can be used to analyze the efficiency of green development of forestry economy.

First, the overall green total factor productivity of the authors’ country's forestry has shown a trend of first decline and then an increase from 2008 to 2018, and there are significant spatiotemporal differences; second, financial support has a significant positive impact on forestry green total factor productivity; third, environmental regulation has a significant threshold effect in the process of financial support on forestry green total factor productivity, and the role of financial support shows a trend of first increasing and then decreasing.

Secondly, taking the data of 30 provinces and cities in the authors’ country from 2008 to 2018 as the research object, using the super-efficiency SBM-Malmquist index to measure the country's forestry green total factor productivity and analyze its temporal and spatial changes; finally, a dynamic panel model was established to explore the impact of financial support on forestry green total factors quantitative impact on productivity, and adding environmental regulation as a threshold variable to establish a dynamic threshold regression, and found that financial support has a nonlinear impact on forestry green total factor productivity.

The purpose of this paper is to explore the effect of monetary policy on bank risk in the banking system in some MENA countries. It explores how some economic and credit indicators affect the level of risk in the banking sector. It combines many factors that could affect banks’ risk appetite such as macroeconomic conditions, banks’ credit size and lending growth. The authors use nonperforming loans as a proxy for banking sector risks. At first, the authors have analyzed the linear relationship between monetary policy and credit risk. As mentioned above, nonlinearity is expected in the underlying relationship, and, thus, they have investigated the nonlinear relationship to deeply analyse the relationship using the dynamic panel threshold model, as stimulated by Kremer et al. (2013). Threshold models have gained a great importance in economics and finance for modelling nonlinear behaviour. Threshold models are useful in showing the turning points in the behaviour of financial and economic indicators. This technique has been applied in this study to study the effect of monetary policy on credit risk.

This paper is divided into the following sections: Section 2 which previews the recent literature; Section 3 which includes some stylized facts about the relationship between credit risk and monetary policy; Section 4 which deals with the model and methodology; Section 5 which handles the data sources and discusses the results, and finally Section 6 which is the conclusion. The paper adopts dynamic panel threshold model of Kremer et al. (2013).

The results show that the relationship between monetary policy and credit risk is positive and significant to a certain threshold, 6.3. If the lending interest rate is higher than 6.3, this increases the credit risk in the banking sector, because increasing the lending interest rate imposes huge burdens on the borrowers, and, therefore, the bad loans and nonperforming loans become more likely. Thus, the MENA countries need to decrease the lending interest rate to be less than 6.3 to reduce the effect of monetary policy on credit risk. Further, these results are qualitatively robust regarding the inclusion of additional control variables, using alternative threshold variables and further endogeneity checks of the credit risk, such as Risk premium and the squared term of the lending interest rate. The results of taking the risk premium and the squared term of the lending interest rate as a threshold served the analysis and confirmed the positive relationship between monetary policy and credit risk above a certain threshold. As for the risk premium, the relationship below the threshold was negative and significant. Other related research points might be a good avenue for the future research such as applying this approach to micro data of banks from different MENA countries. Also, more sophisticated approaches like time-varying panel approach to assess the relationship over the time can be applied.

The importance of this paper lies in the fact that it does not only study the effect of time, but it also focuses on the panel data about some economic and credit indicators in the MENA region for the first time. This is because central banks in the MENA region have common characteristics and congruous level of economic growth. Therefore, to study how the monetary policy affects those countries’ credit risks in their lending policies, this requires careful analysis of how the central banks in this region might behave to control default risks.

Most empirical papers on threshold effects between debt and growth focus on developed countries or a mix of developing and developed economies, often using public debt. Evidence for developing economies is inconclusive, as is the analysis of other threshold effects such as those probably caused by the level of relative development or the repayment capacity. The objective of this study was to examine threshold effects for developing economies, including external and total debt, and identify them in the debt-growth relation considering three determinants: debt itself, initial real Gross Domestic Product (GDP) per capita and debt to exports ratio.

We used a panel threshold regression model (PTRM) and a dynamic panel threshold model (DPTM) for a sample of 47 developing countries from 1970 to 2019.

We found (1) no evidence of threshold effects applying total debt as a threshold variable; (2) one critical value for external debt of 42.32% (using PTRM) and 67.11% (using DPTM), above which this factor is detrimental to growth; (3) two turning points for initial GDP as a threshold variable, where total and external debt positively affects growth at a very low initial GDP, it becomes nonsignificant between critical values, and it negatively influences growth above the second threshold; (4) one critical value for external debt to exports using PTRM and DPTM, below which external debt positively affects growth and negatively above it.

The outcome suggests that only poorer economies can leverage credits. The level of the threshold for the debt to exports ratio is higher than that found in previous literature, implying that the external restriction could be less relevant in recent periods. However, the threshold for the external debt-to-GDP ratio is lower compared to previous evidence.

The purpose of this paper is to investigate the optimal inflation targets for an appropriate exchange rate policy in 15 major oil exporting countries in Sub-Saharan African (SSA).

Dynamic heterogeneous panel threshold techniques are used via threshold-effect test and threshold regression. This procedure is achieved through a grid search and bootstrapping replications method to stimulate the asymptotic distribution of the likelihood ratio test of the null hypothesis on no-threshold as against the alternative hypothesis. The p-values validate the threshold estimates.

Findings revealed that the optimal inflation target has a turning point and its impact on the real exchange rate is up to a threshold level of 14.47 per cent. Furthermore, the inflation rate above the threshold level overwhelmingly revealed its effect on real exchange regimes.

It would have been a good idea to investigate optimal inflation targets for all African countries but due to inadequate data the selection criteria was narrowed to oil-exporting countries in Sub-Saharan Africa.

Inflation targeting beyond the threshold level would have serious implications on the monetary policy.

To the best of the knowledge, this is the first study to look at optimal inflation targets for 15 major oil exporting countries in general and SSA countries in particular. The findings provide a critical analysis of an inflation regime for a typical oil-producing country that oil exports being their source of revenue.

This paper aims to investigate the nonlinear effects of bank regulation stringency on bank lending in 23 sub-Saharan African (SSA) countries over the period 1997–2017.

This study employs the dynamic panel threshold regression (PTR) model, which addresses endogeneity and heterogeneity problems within a nonlinear framework. It also uses indices of entry barriers, mixing of banking and commerce restrictions, activity restrictions and capital regulatory requirements from the updated databases of the World Bank's Bank Regulation and Supervision Surveys as measures of bank regulation.

The linearity test results support the existence of nonlinear effects in the relationship between bank lending and entry barriers or capital regulations in the selected SSA economies. The dynamic PTR estimation results reveal that bank lending responds positively when the stringency of entry barriers is below the threshold of 62.8%. However, once the stringency of entry barriers exceeds that threshold level, bank credit reacts negatively and significantly. By contrast, changes in capital regulation stringency do not affect bank lending, either below or above the obtained threshold value of 76.5%.

These results can help policymakers design bank regulatory measures that will promote the resilience and safety of the banking system but at the same time not bring unintended effects to bank lending.

To the best of the authors’ knowledge, this is the first study to examine the nonlinear effects of bank regulatory measures on bank lending using the dynamic PTR model and SSA context.

This study aims to examine the impact of anti-money laundering (AML) regulations on financial inclusion using a comprehensive measure of AML regulations developed by the Basel Institute on Governance. Again, this study investigates the existence of threshold effects in the AML regulations–financial inclusion nexus.

This study uses panel data across 212 economies (developed, developing and Africa) of the globe-spanning from 2012 to 2019. This study uses the dynamic panel threshold estimation technique proposed by Seo et al. (2019).

In general, the results indicate that AML regulations promote financial inclusion across the globe. However, AML regulations spur financial inclusion below the threshold of AML regulations, whereas, above the thresholds, AML regulations have damaging effects on financial inclusion. Further, the author finds that AML regulations have a detrimental impact on financial inclusion for developed economies. In contrast, AML regulations promote financial inclusion at all levels of AML regulations for African countries.

The findings of this study imply that countries must make conscious efforts in combating the incidence of money laundering by establishing sound AML regulatory regimes as a means of promoting financial inclusiveness. However, there is a need for regulators to ensure cost-effective and efficient implementation of AML regulations.

The value of this paper is its contribution to literature as it is a major attempt in empirically assessing the impact of AML regulations on financial inclusion. Again, to the best of the author’s knowledge, this is the first study to examine the non-linear relationship between AML regulations and financial inclusion.

The study assesses the non-linear nexus between fixed broadband and economic growth. The study focuses on data from 33 African countries for the period 2010 to 2020.

The empirical evidence is based on unit root tests, panel smooth transition regression and the generalized method of moments.

The following findings are established in this study. (1) The proportion of the population with access to electricity above and below which the relationship between fixed broadband and economic growth changes in sign is about 60%. (2) Below this threshold, each 1% increase in fixed broadband subscriptions induces a decline in economic growth of about 2.58%. Above the threshold, economic growth would increase by 2.43% when fixed broadband subscriptions increase by 1%. Sensitivity analyses and generalized method of moments (GMM) estimation show that these results are robust.

Due to the coronavirus disease (COVID-19) pandemic, which requires countries to take adequate measures to curb the spread of the pandemic, especially by means of virtual economic activities, any national policy aiming at improving the access of populations to high levels of fixed broadband services should be preceded by the implementation of an electrification program for at least 60% of the total population. Otherwise, providing a good quality internet connection for the benefit of the population would not produce the expected effects on economic growth and would, therefore, be counterproductive.

This study complements the extant literature by providing thresholds at which fixed broadband affects economic growth.

Taking cues from the fact that there remains a dearth in the establishment of theoretical and empirical relationship between executive compensation and corporate social responsibility (CSR) performance of the firms, this study attempts to explore the non-linear relationship between the said variables.

The study utilizes a strongly balanced panel data set of 179 non-financial National Stock Exchange (NSE) 500 listed firms for the study period of 2015–2020. The study further employs both static as well as Arellano-Bond dynamic panel model under generalized method of moments (GMM) framework to establish the relationship between executive compensation and CSR performance of the sampled firms.

The study acknowledges an inverted U-shaped relationship between executive compensation and environmental, social and governance (ESG) score of the firms. According to the robust estimator, an increase in the level of executive compensation is said to affect CSR performance positively until it surpasses a threshold level of 18.7 percent.

One of the major takeaways that the study provides for the corporate policymakers is that the level of compensation can only motivate the executives to take up socially responsible work up to a certain level surpassing which the executives becomes resistant towards any benefits provided by the CSR performance and get inclined towards economical performances of the firm. At the later stage, the economical expansionary investment benefits overweigh the personal career benefit gained by the executives from the CSR performances of the firm.

The nonlinearity relationship between executive compensation and CSR performance and the threshold level providing the two-fold effect of compensation on the CSR performance of the firms attempted by this study is a rare attempt in an emerging economy like India.